Several technologies exist which can scan the underside of motor vehicles. Many of these technologies rely on the ability to link a vehicle with a vehicle identifier (e.g., license plate number, radio frequency identification (RFID) tag, etc.) so as to be able to perform an automated search of the underside. Other technologies produce only a single image requiring manual inspection of the vehicle image on a screen.
Of those systems that produce an image, the image is typically taken at just one angle (e.g., 90 degree to the horizontal), which allows foreign objects to be hidden in pockets or on cross members under the vehicle, for example. Further, the lighting is often inadequate in such systems to meet the requirements for quality high-resolution images, whether taken at night or during the day. Many such systems rely on ambient light to supplement whatever illumination is provided, and this frequently results in a high number of false positives. Further, many such systems require that a vehicle pass by at a very narrow speed range.
Regarding image storage and retrieval, current systems generally only record images via an archiving function. Where a vehicle identifier is used, an image may be called back from a local database, but not a central database in a networked configuration. Further, systems purporting to automatically detect foreign objects on vehicle undersides fail to show a direct regional comparison between the referenced/archived image and the new image, and do not highlight the targeted region for direct inspection.
There is thus a need for a system and method which resolves the above and other problems in order to provide foreign object detection capabilities and other access control and security benefits associated with vehicle underside detection.